Typical power networks include individual components such as circuit breakers, disconnectors, grounding switches, tie breakers, potential transformers (PT), current transformers (CT), power transformers, overhead lines, underground cables, and the like. An individual component typically handles one function for the power network. The term power network is defined herein as a system having components for transmission and/or distribution of electrical power and includes any portion of the entire power network. For example, the power network may be an entire power transmission and distribution system, a substation, a plurality of substations, a section of a transmission line, a section of a distribution line, and the like.
To determine the reliability of the power network, reliability parameters are typically determined for each of the individual components. To quantify the frequency and the amount of time that a component is expected to be unavailable in the power network (e.g., due to a failure or maintenance), a reliability assessment may be performed to calculate some reliability measure for each component in the power network. For example, a reliability assessment system may calculate, for each component a total outage frequency (e.g., the expected number of times that a component will be de-energized per year). The total outage frequency may include a component failure rate (e.g., the expected number of times that a component will be de-energized due to a component fault, the probability of component failure in a given time period, and the like), a self maintenance outage frequency (e.g., the expected number of times that a component will be de-energized due to a maintenance of that component), another maintenance frequency (e.g., the expected number of times that a component will be de-energized due to maintenance of another component), and the like. These reliability parameters may be determined through data mining, processing historical equipment failures (e.g., via failure records, utility outage management systems), and the like.
Current systems for reliability analysis, however, treat all components of the same type as having the same reliability parameters, regardless of the component's condition. The condition of a component may have a great effect on the failure rate of a component. For example, a component that has been well maintained is probably not as likely to fail as a component that has been completely neglected. By ignoring such factors, conventional reliability assessments may yield inaccurate results. Other component conditions, such as, for example, environmental and operational conditions are not considered by conventional systems. Moreover, many components include a large variety of subcomponents, each which can affect the failure rate of the overall component. Each of these subcomponents may have been maintained differently and have a different condition. Conventional systems do not address these factors either. With the recent deregulation of power utilities, accurate reliability assessment of power networks is critical for success in the market.
Many reliability assessment systems rely on failure rates in determining other reliability indices, performing root cause analysis to identify components with the largest impact on failure rates, performing sensitivity analysis to study possible impacts of changes in component failure rates, performing failure risk assessment based on Monte Carlo analysis, and the like. As can be appreciated, determining an accurate failure rate may be very important to many types of reliability assessments.
Therefore, a need exists for a system and method for reliability assessment that can take into consideration the condition of power network components and subcomponents.